Gadolinium-enhanced echo-planar T2-weighted MRI of tumors in the extracranial head and neck: Feasibility study and preliminary results using a distributed-parameter tracer kinetic analysis

Joint Optimization of k-t Sampling Pattern and Reconstruction of DCE MRI for Pharmacokinetic Parameter Estimation

This work proposes to develop and evaluate a deep learning framework that jointly optimizes k-t sampling patterns and reconstruction for head and neck dynamic contrast-enhanced (DCE) MRI aiming to reduce bias and uncertainty of pharmacokinetic (PK) parameter estimation. 2D Cartesian phase encoding k-space subsampling patterns for a 3D spoiled gradient recalled echo (SPGR) sequence along a time course of DCE MRI were jointly optimized in a deep learning-based dynamic MRI reconstruction network by a loss function concerning both reconstruction image quality and PK parameter estimation accuracy. During training, temporal k-space data sharing scheme was optimized as well. The proposed method was trained and tested by multi-coil complex digital reference objects of DCE images (mcDROs). The PK parameters estimated by the proposed method were compared with two published iterative DCE MRI reconstruction schemes using normalized root mean squared errors (NRMSEs) and Bland-Altman analysis at temporal resolutions of [Formula: see text] = 2s, 3s, 4s, and 5s, which correspond to undersampling rates of R = 50, 34, 25, and 20. The proposed method achieved low PK parameter NRMSEs at all four temporal resolutions compared with the benchmark methods on testing mcDROs. The Bland-Altman plots demonstrated that the proposed method reduced PK parameter estimation bias and uncertainty in tumor regions at temporal resolution of 2s. The proposed method also showed robustness to contrast arrival timing variations across patients. This work provides a potential way to increase PK parameter estimation accuracy and precision, and thus facilitate the clinical translation of DCE MRI.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer

Dynamic contrast-enhanced computed tomography (DCE-CT) and magnetic resonance imaging (DCE-MRI) are functional imaging techniques. They aim to characterise the microcirculation by applying the principles of tracer-kinetic analysis to concentration-time curves measured in individual image pixels. In this paper, we review the basic principles of DCE-MRI and DCE-CT, with a specific emphasis on the use of tracer-kinetic modeling. The aim is to provide an introduction to the field for a broader audience of pharmacokinetic modelers. In a first part, we first review the key aspects of data acquisition in DCE-CT and DCE-MRI, including a review of basic measurement strategies, a discussion on the relation between signal and concentration, and the problem of measuring reference data in arterial blood. In a second part, we define the four main parameters that can be measured with these techniques and review the most common tracer-kinetic models that are used in this field. We first discuss the models for the capillary bed and then define the most general four-parameter models used today: the two-compartment exchange model, the tissue-homogeneity model, the "adiabatic approximation to the tissue-homogeneity model" and the distributed-parameter model. In simpler tissue types or when the data quality is inadequate to resolve all the features of the more complex models, it is often necessary to resort to simpler models, which are special cases of the general models and hence have less parameters. We discuss the most common of these special cases, i.e. the uptake models, the extended Tofts model, and the one-compartment model. Models for two specific tissue types, liver and kidney, are discussed separately. We conclude with a review of practical aspects of DCE-CT and DCE-MRI data analysis, including the problem of identifying a suitable model for any given data set, and a brief discussion of the application of tracer-kinetic modeling in the context of drug development. Here, an important application of DCE techniques is the derivation of quantitative imaging biomarkers for the assessment of effects of targeted therapeutics on tumors.

Biologic imaging of head and neck cancer: the present and the future

While anatomic imaging (CT and MR imaging) of HNC is focused on diagnosing and/or characterizing the disease, defining its local extent, and evaluating distant spread, accurate assessment of the biologic status of the cancer (cellularity, growth rate, response to nonsurgical chemoradiation therapy, and so forth) can be invaluable for prognostication, planning therapy, and follow-up of lesions after therapy. The combination of anatomic and biologic imaging techniques can thus provide a more comprehensive evaluation of the patient. The purpose of this work was to review the present and future clinical applications of advanced biologic imaging techniques in HNC evaluation and management. As part of the biologic imaging array, we discuss MR spectroscopy, diffusion and perfusion MR imaging, CTP, and FDG-PET scanning and conclude with exciting developments that hold promise in assessment of tumor hypoxia and neoangiogenesis.

Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability

The tracer-kinetic models developed in the early 1990s for dynamic contrast-enhanced MRI (DCE-MRI) have since become a standard in numerous applications. At the same time, the development of MRI hardware has led to increases in image quality and temporal resolution that reveal the limitations of the early models. This in turn has stimulated an interest in the development and application of a second generation of modelling approaches. They are designed to overcome these limitations and produce additional and more accurate information on tissue status. In particular, models of the second generation enable separate estimates of perfusion and capillary permeability rather than a single parameter K(trans) that represents a combination of the two. A variety of such models has been proposed in the literature, and development in the field has been constrained by a lack of transparency regarding terminology, notations and physiological assumptions. In this review, we provide an overview of these models in a manner that is both physically intuitive and mathematically rigourous. All are derived from common first principles, using concepts and notations from general tracer-kinetic theory. Explicit links to their historical origins are included to allow for a transfer of experience obtained in other fields (PET, SPECT, CT). A classification is presented that reveals the links between all models, and with the models of the first generation. Detailed formulae for all solutions are provided to facilitate implementation. Our aim is to encourage the application of these tools to DCE-MRI by offering researchers a clearer understanding of their assumptions and requirements.

Dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors: a pilot study

PURPOSE

To preliminarily investigate the utility of dynamic susceptibility contrast perfusion MR imaging in distinguishing malignant from benign head and neck tumors.

MATERIAL AND METHODS

Seventy eight patients with head and neck masses underwent single shot dynamic susceptibility contrast T2*-weighted perfusion weighted MR imaging after bolus infusion of gadolinium-DTPA was administrated. The signal intensity time curve of the lesion was created. Dynamic susceptibility contrast percentage (DSC%) was calculated and correlated with pathological findings.

RESULTS

The mean DSC% of malignant tumor (n=40) was 39.3±9.6% and of benign lesions (n=38) was 24.3±10.3%. There was a statistically significant difference of the DSC% between benign and malignant tumors (P=0.001) and within benign tumors (P=0.001). When DSC% of 30.7% was used as a threshold for differentiating malignant from benign tumors, the best results were obtained: accuracy of 84.6%, sensitivity of 80% and specificity of 89.2%.

CONCLUSION

Dynamic susceptibility contrast perfusion weighted MR imaging is a non-invasive imaging technique that can play a role in differentiation between malignant and benign head and neck tumors.

Functional imaging of head and neck cancers

PURPOSE OF REVIEW

Functional imaging including single photon emission computed tomography, PET and MRI techniques in head and neck squamous cell cancer allows disease characterization beyond structure and morphology.

RECENT FINDINGS

In patients without clinical signs of lymph node involvement, sensitivity of fluoro-2-deoxy-D-glucose PET is only 50%. This has led to the use of sentinel lymph node scintigraphy that seems to be a valid alternative to elective stage dissection. Additionally, the use of single-photon emission computed tomography-computed tomography imaging enables a more accurate localization of the sentinel lymph node scintigraphy. The fluoro-2-deoxy-D-glucose uptake intensity of the head and neck squamous cell carcinoma sites is related to locoregional control and overall survival. In case of suspicion for residual or recurrent head and neck squamous cell carcinoma after surgery or (chemo)radiotherapy, fluoro-2-deoxy-D-glucose-PET has a high sensitivity and seems to be cost-effective in selecting patients for direct laryngoscopy. Diffusion-weighted MRI in combination with size and morphological criteria is a strong predictor of presence of malignant lymph nodes. Initial reports indicate the use of diffusion-weighted imaging for response assessment as early as 1 week after beginning of radiochemotherapy. Perfusion MRI is studied for the measurement of drug effects on tumour (micro)vascularity and capillary permeability.

SUMMARY

Functional imaging improves the initial staging and the detection of residual or recurrent disease following therapy.